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Deep sequencing identification of miRNAs in pigeon ovaries illuminated with monochromatic light

Overview of attention for article published in BMC Genomics, June 2018
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Title
Deep sequencing identification of miRNAs in pigeon ovaries illuminated with monochromatic light
Published in
BMC Genomics, June 2018
DOI 10.1186/s12864-018-4831-6
Pubmed ID
Authors

Ying Wang, Hai-ming Yang, Wei Cao, Yang-bai Li, Zhi-yue Wang

Abstract

The use of light of different wavelengths has grown popular in the poultry industry. An optimum wavelength is believed to improve pigeon egg production, but little is known about the role of microRNAs (miRNAs) in the effects of monochromatic light on ovarian pigeon function. Herein, we harvested ovaries from pigeons reared under monochromatic light of different wavelength and performed deep sequencing on various tissues using an Illumina Solexa high-throughput instrument. We obtained 66,148,548, 67,873,805, and 71,661,771 clean reads from ovaries of pigeons reared under red light (RL), blue light (BL), and white light (WL), respectively. We identified 1917 known miRNAs in nine libraries, of which 524 were novel. Three and five differentially expressed miRNAs were identified in BL vs. WL and RL vs. WL groups, respectively. Quantitative reverse transcription PCR was used to validate differentially expressed miRNAs (miR-200, miR-122, and miR-205b). In addition, 5824 target genes were annotated as differentially expressed miRNAs, most of which are involved in reproductive pathways including oestrogen signalling, cell cycle, and oocyte maturation. Notably, ovarian miR-205b expression was significantly negatively correlated with its target 11β-hydroxysteroid dehydrogenase type 1 (HSD11B1). miRNA-mRNA network analysis suggests that miR-205b targeting of HSD11B1 plays a key role in the effects of monochromatic light on pigeon egg production. These findings indicate that monochromatic light shortens the oviposition interval of pigeons, which may be useful for egg production and pigeon breeding.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Student > Ph. D. Student 2 20%
Student > Bachelor 1 10%
Other 1 10%
Student > Postgraduate 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 20%
Agricultural and Biological Sciences 2 20%
Chemical Engineering 1 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Veterinary Science and Veterinary Medicine 1 10%
Other 3 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 June 2018.
All research outputs
#21,264,673
of 23,881,329 outputs
Outputs from BMC Genomics
#9,455
of 10,793 outputs
Outputs of similar age
#291,839
of 331,047 outputs
Outputs of similar age from BMC Genomics
#206
of 244 outputs
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So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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